The @datologyai team tested their Curation Studio at scale by generating large amounts of synthetic data on Modal, scaling to hundreds of B300s on demand.
Today, we’re excited to launch the Datology Curation Studio, customizable frontier data curation for every team training its own models.
Data quality is the ultimate compute multiplier, and Curation Studio makes it easy for everyone.
From frogs to the frontier, @ScottWu46 covered a lot at Runtime:
→ Agents are moving from tab completion to “virtual employees” that own outcomes
→ Frontier models may only need ~2% of workloads; routing handles the rest
→ 91% of Cognition’s internal Devin sessions start
See how @ProximalHQ built a custom post-training stack with Modal Clusters for on-demand multi-node clusters, and autoscaling GPUs to handle bursty inference workloads.
At Proximal, we believe that building our own research infrastructure is crucial to design the highest-quality training data
Today, we are sharing more information about our internal post-training stack
Congratulations to @DecagonAI on the launch of Chord.
Trained and served on Modal, Chord sees low time-to-first-audio even during massive swings in concurrency.
Meet Chord, our new speech model by the Decagon Labs team.
Post-trained to preserve pace and voice naturalness, Chord has increased resolution rates in every deployment it was used in.